Tumor purity adjusted beta values improve biological interpretability of high-dimensional DNA methylation data
(2022) In PLoS ONE 17(9 September).- Abstract
A common issue affecting DNA methylation analysis in tumor tissue is the presence of a substantial amount of non-tumor methylation signal derived from the surrounding microenvironment. Although approaches for quantifying and correcting for the infiltration component have been proposed previously, we believe these have not fully addressed the issue in a comprehensive and universally applicable way. We present a multi-population framework for adjusting DNA methylation beta values on the Illumina 450/850K platform using generic purity estimates to account for non-tumor signal. Our approach also provides an indirect estimate of the aggregate methylation state of the surrounding normal tissue. Using whole exome sequencing derived purity... (More)
A common issue affecting DNA methylation analysis in tumor tissue is the presence of a substantial amount of non-tumor methylation signal derived from the surrounding microenvironment. Although approaches for quantifying and correcting for the infiltration component have been proposed previously, we believe these have not fully addressed the issue in a comprehensive and universally applicable way. We present a multi-population framework for adjusting DNA methylation beta values on the Illumina 450/850K platform using generic purity estimates to account for non-tumor signal. Our approach also provides an indirect estimate of the aggregate methylation state of the surrounding normal tissue. Using whole exome sequencing derived purity estimates and Illumina 450K methylation array data generated by The Cancer Genome Atlas project (TCGA), we provide a demonstration of this framework in breast cancer illustrating the effect of beta correction on the aggregate methylation beta value distribution, clustering accuracy, and global methylation profiles.
(Less)
- author
- Staaf, Johan
LU
and Aine, Mattias LU
- organization
- publishing date
- 2022-09
- type
- Contribution to journal
- publication status
- published
- subject
- in
- PLoS ONE
- volume
- 17
- issue
- 9 September
- article number
- e0265557
- publisher
- Public Library of Science (PLoS)
- external identifiers
-
- scopus:85137686539
- pmid:36084090
- ISSN
- 1932-6203
- DOI
- 10.1371/journal.pone.0265557
- language
- English
- LU publication?
- yes
- id
- 30ef794d-3cde-48db-a3ce-10b469dc9a3b
- date added to LUP
- 2022-11-30 11:08:35
- date last changed
- 2025-02-05 20:23:52
@article{30ef794d-3cde-48db-a3ce-10b469dc9a3b, abstract = {{<p>A common issue affecting DNA methylation analysis in tumor tissue is the presence of a substantial amount of non-tumor methylation signal derived from the surrounding microenvironment. Although approaches for quantifying and correcting for the infiltration component have been proposed previously, we believe these have not fully addressed the issue in a comprehensive and universally applicable way. We present a multi-population framework for adjusting DNA methylation beta values on the Illumina 450/850K platform using generic purity estimates to account for non-tumor signal. Our approach also provides an indirect estimate of the aggregate methylation state of the surrounding normal tissue. Using whole exome sequencing derived purity estimates and Illumina 450K methylation array data generated by The Cancer Genome Atlas project (TCGA), we provide a demonstration of this framework in breast cancer illustrating the effect of beta correction on the aggregate methylation beta value distribution, clustering accuracy, and global methylation profiles.</p>}}, author = {{Staaf, Johan and Aine, Mattias}}, issn = {{1932-6203}}, language = {{eng}}, number = {{9 September}}, publisher = {{Public Library of Science (PLoS)}}, series = {{PLoS ONE}}, title = {{Tumor purity adjusted beta values improve biological interpretability of high-dimensional DNA methylation data}}, url = {{http://dx.doi.org/10.1371/journal.pone.0265557}}, doi = {{10.1371/journal.pone.0265557}}, volume = {{17}}, year = {{2022}}, }